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At least 1,171 records · Page 65

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NASA NTRS2005

Inference of Ice Cloud Properties from High-spectral Resolution Infrared Observations

The theoretical basis is explored for inferring the microphysical properties of ice crystal from high-spectral resolution infrared observations. A radiative transfer model is employed to simulate spectral radiances to address relevant issues. The extinction and absorption efficiencies of individual ice crystals, assumed as hexagonal columns for large particles and droxtals for small particles, are computed from a combination of the finite- difference time-domain (FDTD) technique and a composite method. The corresponding phase functions are computed from a combination of FDTD and an improved geometric optics method (IGOM). Bulk scattering properties are derived by averaging the single- scattering properties of individual particles for 30 particle size distributions developed from in situ measurements and for additional four analytical Gamma size distributions for small particles. The non-sphericity of ice crystals is shown to have a significant impact on the radiative signatures in the infrared (IR) spectrum; the spherical particle approximation for inferring ice cloud properties may result in an overest&ation of the optical thickness and an inaccurate retrieval of effective particle size. Furthermore, we show that the error associated with the use of the Henyey-Greenstein phase function can be as larger as 1 K in terms of brightness temperature for larger particle effective size at some strong scattering wavenumbers. For small particles, the difference between the two phase functions is much less, with brightness temperatures generally differing by less than 0.4 K. The simulations undertaken in this study show that the slope of the IR brightness temperature spectrum between 790-960/cm is sensitive to the effective particle size. Furthermore, a strong sensitivity of IR brightness temperature to cloud optical thickness is noted within the l050-1250/cm region. Based on this spectral feature, a technique is presented for the simultaneous retrieval of the visible optical thickness and effective particle size from high spectral resolution infrared data under ice cloudy con&tion. The error analysis shows that the uncertainty of the retrieved optical thickness and effective particle size has a small range of variation. The error for retrieving particle size in conjunction with an uncertainty of 5 K in cloud'temperature, or a surface temperature uncertainty of 2.5 K, is less than 15%. The corresponding e m r in the uncertainty of optical thickness is within 5-2096, depending on the value of cloud optical thickness. The applicability of the technique is demonstrated using the aircraft-based High- resolution Interferometer Sounder (HIS) data from the Subsonic Aircraft: Contrail and Cloud Effects Special Study (SUCCESS) in 1996 and the First ISCCP Regional Experiment - Arctic Clouds Experiment (FIRE-ACE) in 1998.

Huang, Hung-Lung↗

NASA NTRS2011

The Extreme Spin of the Black Hole in Cygnus X-1

The compact primary in the X-ray binary Cygnus X-1 was the first black hole to be established via dynamical observations. We have recently determined accurate values for its mass and distance, and for the orbital inclination angle of the binary. Building on these results, which are based on our favored (asynchronous) dynamical model, we have measured the radius of the inner edge of the black hole s accretion disk by fitting its thermal continuum spectrum to a fully relativistic model of a thin accretion disk. Assuming that the spin axis of the black hole is aligned with the orbital angular momentum vector, we have determined that Cygnus X-1 contains a near-extreme Kerr black hole with a spin parameter a* > 0.95 (3(sigma)). For a less probable (synchronous) dynamical model, we find a. > 0.92 (3 ). In our analysis, we include the uncertainties in black hole mass, orbital inclination angle, and distance, and we also include the uncertainty in the calibration of the absolute flux via the Crab. These four sources of uncertainty totally dominate the error budget. The uncertainties introduced by the thin-disk model we employ are particularly small in this case given the extreme spin of the black hole and the disk s low luminosity.

Gou, Lijun↗

NASA NTRS2005

The Extreme Spin of the Black Hole in Cygnus X-1

The compact primary in the X-ray binary Cygnus X-1 was the first black hole to be established via dynamical observatIOns. We have recently determined accurate values for its mass and distance, and for the orbital inclination angle of the binary. Building on these.results, which are based on our favored (asynchronous) dynamical model, we have measured the radius of the inner edge of the black hole's accretion disk by fitting its thermal continuum.spectrum to a fully relativistic model of a thin accretion disk. Assuming that the spin axis of the black hole is aligned with the orbital angular momentum vector, we have determined that Cygnus X-I contains a near-extreme Kerr black hole with a spin parameter a* > 0.95 (3(sigma)). For a less probable (synchronous) dynamIcal model, we find a* > 0.92 (3(sigma)). In our analysis, we include the uncertainties in black hole mass orbital inclination angle and distance, and we also include the uncertainty in the calibration of the absolute flux via the Crab. These four sources of uncertainty totally dominate the error budget. The uncertainties introduced by the thin-disk model we employ are particularly small in this case given the extreme spin of the black hole and the disk's low luminosity.

Gou, Lijun↗

NASA NTRS2012

Real-Time X-ray Radiography Diagnostics of Components in Solid Rocket Motors

Solid rocket motors (SRMs) typically use nozzle materials which are required to maintain their shape as well as insulate the underlying support structure during the motor operation. In addition, SRMs need internal insulation materials to protect the motor case from the harsh environment resulting from the combustion of solid propellant. In the nozzle, typical materials consist of high density graphite, carbon-carbon composites and carbon phenolic composites. Internal insulation of the motor cases is typically a composite material with carbon, asbestos, Kevlar, or silica fibers in an ablative matrix such as EPDM or NBR. For both nozzle and internal insulation materials, the charring process occurs when the hot combustion products heat the material intensely. The pyrolysis of the matrix material takes away a portion of the thermal energy near the wall surface and leaves behind a char layer. The fiber reinforcement retains the porous char layer which provides continued thermal protection from the hot combustion products. It is of great interest to characterize both the total erosion rates of the material and the char layer thickness. By better understanding of the erosion process for a particular ablative material in a specific flow environment, the required insulation material thickness can be properly selected. The recession rates of internal insulation and nozzle materials of SRMs are typically determined by testing in some sort of simulated environment; either arc-jet testing, flame torch testing, or subscale SRMs of different size. Material recession rates are deduced by comparison of pre- and post-test measurements and then averaging over the duration of the test. However, these averaging techniques cannot be used to determine the instantaneous recession rates of the material. Knowledge of the variation in recession rates in response to the instantaneous flow conditions during the motor operation is of great importance. For example, in many SRM configurations the recession of the solid propellant grain can drastically alter the flow-field and effect the recession of internal insulation and nozzle materials. Simultaneous measurement of the overall erosion rate, the development of the char layer, and the recession of the char-virgin interface during the motor operation can be rather difficult. While invasive techniques have been used with limited success, they have serious drawbacks. Break wires or make wire sensors can be installed into a sufficient number of locations in the charring material from which a time history of the charring surface can be deduced. These sensors fundamentally alter the local structure of the material in which they are imbedded. Also, the location of these sensors within the material is not known precisely without the use of an X-ray. To determine instantaneous recession rates, real-time X-ray radiography (X-ray RTR) has been utilized in several SRM experiments at PSU. The X-ray RTR system discussed in this paper consists of an X-ray source, X-ray image intensifier, and CCD camera connected to a capture computer. The system has been used to examine the ablation process of internal insulation as well as nozzle material erosion in a subscale SRM. The X-ray source is rated to 320 kV at 10 mA and has both a large (5.5 mm) and small (3.0 mm) focal spot. The lead-lined cesium iodide X-ray image intensifier produces an image which is captured by a CCD camera with a 1,000 x 1,000 pixel resolution. To produce accurate imagery of the object of interest, the alignment of the X-ray source to the X-ray image intensifier is crucial. The image sequences captured during the operation of an SRM are then processed to enhance the quality of the images. This procedure allows for computer software to extract data on the total erosion rate and the char layer thickness. Figure 1 Error! Reference source not found.shows a sequence of images captured during the operation the subscale SRM with the X-ray RTR system. The X-rayTR system, alignment procedure, uncertainty determination, and image analysis process will be discussed in detail in the full manuscript.

Cortopassi, A. C.↗

NASA NTRS2013

The Challenges of Credible Thermal Protection System Reliability Quantification

The paper discusses several of the challenges associated with developing a credible reliability estimate for a human-rated crew capsule thermal protection system. The process of developing such a credible estimate is subject to the quantification, modeling and propagation of numerous uncertainties within a probabilistic analysis. The development of specific investment recommendations, to improve the reliability prediction, among various potential testing and programmatic options is then accomplished through Bayesian analysis.

Green, Lawrence L.↗

NASA NTRS2014

The Evolution of the Galaxy Rest-Frame Ultraviolet Luminosity Function Over the First Two Billion Years

We present a robust measurement and analysis of the rest-frame ultraviolet (UV) luminosity function at z = 4 to 8. We use deep Hubble Space Telescope imaging over the CANDELS/GOODS fields, the Hubble Ultra Deep Field and the Hubble Frontier Field deep parallel observations near the Abell 2744 and MACS J0416.1- 2403 clusters. The combination of these surveys provides an effective volume of 0.6-1.2 ×10(exp 6) Mpc(exp 3) over this epoch, allowing us to perform a robust search for bright (M(sub UV) less than −21) and faint (M(sub UV) = −18) galaxies. We select galaxies using a well-tested photometric redshift technique with careful screening of contaminants, finding a sample of 7446 galaxies at 3.5 less than z less than 8.5, with more than 1000 galaxies at z of approximately 6 - 8. We measure both a stepwise luminosity function for galaxies in our redshift samples, as well as a Schechter function, using a Markov Chain Monte Carlo analysis to measure robust uncertainties. At the faint end our UV luminosity functions agree with previous studies, yet we find a higher abundance of UV-bright galaxies at z of greater than or equal to 6. Our bestfit value of the characteristic magnitude M* is consistent with −21 at z of greater than or equal to 5, different than that inferred based on previous trends at lower redshift. At z = 8, a single power-law provides an equally good fit to the UV luminosity function, while at z = 6 and 7, an exponential cutoff at the bright-end is moderately preferred. We compare our luminosity functions to semi-analytical models, and find that the lack of evolution in M* is consistent with models where the impact of dust attenuation on the bright-end of the luminosity function decreases at higher redshift, though a decreasing impact of feedback may also be possible. We measure the evolution of the cosmic star-formation rate (SFR) density by integrating our observed luminosity functions to M(sub UV) = −17, correcting for dust attenuation, and find that the SFR density declines proportionally to (1 + z)((exp −4.3)(+/-)(0.5)) at z greater than 4, consistent with observations at z greater than or equal to 9. Our observed luminosity functions are consistent with a reionization history that starts at redshift of approximately greater than 10, completes at z greater than 6, and reaches a midpoint (x(sub HII) = 0.5) at 6.7 less than z less than 9.4. Finally, using a constant cumulative number density selection and an empirically derived rising star-formation history, our observations predict that the abundance of bright z = 9 galaxies is likely higher than previous constraints, though consistent with recent estimates of bright z similar to 10 galaxies.

Galaxy↗

NASA NTRS2017

Determining the Optimal Spectral Sampling Frequency and Uncertainty Thresholds for Hyperspectral Remote Sensing of Ocean Color

Using a modified geostatistical technique, empirical variograms were constructed from the first derivative of several diverse remote sensing reflectance and phytoplankton absorbance spectra to describe how data points are correlated with distance across the spectra. The maximum rate of information gain is measured as a function of the kurtosis associated with the Gaussian structure of the output, and is determined for discrete segments of spectra obtained from a variety of water types (turbid river filaments, coastal waters, shelf waters, a dense Microcystis bloom, and oligotrophic waters), as well as individual and mixed phytoplankton functional types (PFTs; diatoms, chlorophytes, cyanobacteria, coccolithophores). Results show that a continuous spectrum of 5 to 7 nm spectral resolution is optimal to resolve the variability across mixed reflectance and absorbance spectra. In addition, the impact of uncertainty on subsequent derivative analysis is assessed, showing that a limit of 3 Gaussian noise (SNR 66) is tolerated without smoothing the spectrum, and 13 (SNR 15) noise is tolerated with smoothing.

Noise in imaging systems↗

NASA NTRS2019

Hybrid Transportation System Integrated Trajectory Design and Optimization for Mars Landing Site Accessibility

NASA’s Mars Study Capability Team continues the agency’s efforts to study and refine the nation’s plan to field a sustainable human Mars campaign. One of the primary open issues left unanswered during previous analysis cycles was the uncertainty of the impact to the vehicle performance requirement to deliver crew and cargo to the same landing site across multiple mission opportunities. The Mars Study Capability Team has recently developed an integrated trajectory optimization and system closure model to solve the complex interplanetary trajectory optimization using both low-thrust and high-thrust maneuvers. This paper demonstrates the capability of this new integrated trajectory design and optimization method as it applies to the landing site accessibility problem for the Hybrid transportation architecture. The results showed that the current vehicle is capable of reaching up to +20 degree latitude and down to -20 degree latitude in every mission opportunity from 2033 to 2052. However, reaching latitudes beyond +/- 20 required more propellant than the spacecraft is currently designed to carry for many of the mission opportunities.

Chai, Patrick R.↗

NASA NTRS2022

MLtool: Universal Supervised Machine Learning Tool to Model Tabulated Data

Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

Machine learning↗

NASA NTRSDate not supplied

Envisioning the Future of International Earth Observations Collaboration: Area and Map Accuracy Estimation by Sampling

- Maps have errors, sometimes a lot of errors ⇒ obtaining information directly from map problematic; any use of the map will benefit from information about errors/uncertainty - IPCC: unbiasedness and uncertainty - By randomly drawing a sample from the study area, observing reference conditions at drawn locations, and constructing estimators – easily estimate areas and map accuracy ± uncertainty - Sampling design and analysis, relatively easy – collecting reference observations is not. Cloud-based solutions, e.g. AREA2, Collect Earth Online, facilitate the collection of reference observations - More research and guidance needed!

Pontus Olofsson↗

NASA NTRS2022

MLtool Python Code

Machine Learning↗

NASA NTRSDate not supplied

Aerothermal Analysis and Thermal Protection System Design of the Mars Sample Retrieval Lander [SRL].

Mars Sample Retrieval Lander, part of the Mars Sample Return (MSR) mission, is being designed to land the heaviest payload yet, to the surface of Mars. SRL is being designed to carry the Lander, Sample Transfer System, Mars Acent Vehicle, and two Sample Recovery Helicopters. Compared to MSL and Mars 2020, SRL has a significantly higher ballistic coefficient, and flies at a higher lift/drag configuration. While the SRL heatshield is very similar to that of MSL and M2020, the backshell is very different, so as to accommode the payload. SRL is shielded by the same TPS materials as MSL and Mars 2020, with changes to design reflecting the SRL configuration and ConOPS. The aerothermal analysis and TPS design methodology of SRL relies on the successes of MSL and Mars 2020, and the lessons learned from MEDLI and MEDLI2. However, the constraints on mass require us to revisit all of our prediction models and analysis assumptions, in an attempt to reduce conservatism and TPS mass. MSL and Mars 2020 reconstruction, and detailed comparisons against MEDLI/MEDLI2 data are being used to justify our analysis approach and refine uncertainties and margins.

Mars↗

NASA NTRSDate not supplied

Reduction of Aircraft Noise Uncertainty for a Notional Supersonic Business Jet

NASA supported a study by the International Civil Aviation Organization on the environmental impact of adding supersonic aircraft to the existing global fleet by designing a notional 55-tonne supersonic business jet. The aircraft is referred to as the Supersonic Technology Concept Aeroplane (STCA) and has been used in a multitude of studies over the past few years. One of the many studies on this aircraft was the noise produced by the STCA during landing and take-off (LTO) operations. The LTO noise for the STCA was assessed using contemporary noise prediction tools that have been primarily developed for and utilized by subsonic aircraft, resulting in a high level of uncertainty for the STCA noise predictions. NASA has recently been conducting research and developing tools to reduce the uncertainty for airport noise predictions of supersonic aircraft. The initial focus of the uncertainty reduction was on the jet and inlet-radiated fan noise produced by supersonic engine systems since these sources are dominant during take-off and landing operations for supersonic jets. The results of these efforts are discussed and applied to the STCA model to update the airport noise predictions and associated uncertainty metrics. It is shown that by using new noise source prediction models, the overall system-level cumulative noise uncertainty of the study vehicle is reduced from a standard deviation of 7.8 EPNdB to 2.0 EPNdB.

uncertainty↗

DOE OSTI2020

Safeguards Modeling for Advanced Nuclear Facility Design.

Future nuclear fuel cycle facilities will see a significant benefit from considering materials accountancy requirements early in the design process. The Material Protection, Accounting, and Control Technologies (MPACT) working group is demonstrating Safeguards and Security by Design (SSBD) for a notional electrochemical reprocessing facility as part of a 2020 Milestone. The idea behind SSBD is to consider regulatory requirements early in the design process to provide more optimized systems and avoid costly retrofits later in the design process. Safeguards modeling, using single analyst tools, allows the designer to efficiently consider materials accountancy approaches that meet regulatory requirements. However, safeguards modeling also allows the facility designer to go beyond current regulations and work toward accountancy designs with rapid response and lower thresholds for detection of anomalies. This type of modeling enables new safeguards approaches and may inform future regulatory changes. The Separation and Safeguards Performance Model (SSPM) has been used for materials accountancy system design and analysis. This paper steps through the process of designing a Material Control and Accountancy (MC&A) system, presents the baseline system design for an electrochemical reprocessing facility, and provides performance metrics from the modeling analysis. The most critical measurements in the electrochemical facility are the spent fuel input, electrorefiner salt, and U/TRU product output measurements. Finally, material loss scenario analysis found that measurement uncertainties (relative standard deviations) for Pu would need to be at 1% (random and systematic error components) or better in order to meet domestic detection goals or as high as 3% in order to meet international detection goals, based on a 100 metric ton per year plant size.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

NASA NTRS2020

How Long Is Too Long? Variogram Analysis of AERONET Data to Aid Aerosol Validation and Intercomparison Studies

Geophysical data sets derived from satellite sensors, ground/airborne instrumentation, and computational models are often compared against each other. A common example is the validation of satellite aerosol optical depth (AOD) retrievals against measurements from Aerosol Robotic Network (AERONET) Sun photometers. Spatiotemporal mismatch between data set sampling means that uncaptured variation in the underlying geophysical field introduces apparent disagreement into such comparisons, known as representation or collocation matchup uncertainty. This study uses variogram analysis of AERONET data to estimate temporal mismatch uncertainties and decorrelation time scales for the global AERONET record. As well as total AOD, the fine‐ and coarse‐mode AODs, Ångström Exponent (AE), and fine‐mode fraction (FMF) of AOD are analyzed. Globally, a time difference of 30 min typically induces from 0.011–0.035 variation in AOD. For total, fine, and coarse AODs the typical time to decorrelation is around 2–10 days. For AE and FMF it is 3–33 days; that is, aerosol systems often persist significantly longer than individual events in them. Biomass burning regions tend to show the largest and fastest subdaily AOD variability and also longest times to decorrelation. Some sites show significant season‐to‐season variations in behavior. These results can be used to inform site‐specific time collocation thresholds for aerosol validation analyses and account for temporal variation when estimating data set uncertainty. They also have implications for comparisons between different satellite products or models, data aggregation, and time series analyses. Results are provided on a site‐by‐site basis to facilitate use by other researchers.

satellite↗

NASA NTRS2018

Multifidelity Uncertainty Quantification of a Commercial Supersonic Transport

The objective of this work was to develop a multifidelity uncertainty quantification approach for efficient analysis of a commercial supersonic transport concept. An approach based on point-collocation, non-intrusive polynomial chaos was formulated in which a low-fidelity model could be corrected using multiple higher-fidelity models. The formulation and methodology also allows for the addition of uncertainty sources not present in the lower fidelity models. To demonstrate the applicability and potential computational savings of the multifidelity polynomial chaos approach, two model problems were explored. The first was a supersonic airfoil with three levels of modeling fidelity, each capturing a gradual increase in modeling of the underlying flow physics. As much as 50% computational cost reduction was observed using the mutlifidelity approach, while predicting nearly the same amount of uncertainty in drag. The second problem was a commercial supersonic transport. This model had three levels of fidelity that included two different modeling approaches and the addition of physics between the fidelity levels. Results of this analysis yielded nearly a 70% computational savings to predict a comparable amount of uncertainty in ground noise. Both problems illustrate the applicability and significant computational savings of the multifidelity method for efficient and accurate uncertainty quantification.

Thomas K. West IV↗

DOE OSTI2021

Thermonuclear neutron emission from a sheared-flow stabilized Z-pinch

We report the fusion Z-pinch experiment (FuZE) is a sheared-flow stabilized Z-pinch designed to study the effects of flow stabilization on deuterium plasmas with densities and temperatures high enough to drive nuclear fusion reactions. Results from FuZE show high pinch currents and neutron emission durations thousands of times longer than instability growth times. While these results are consistent with thermonuclear neutron emission, energetically resolved neutron measurements are a stronger constraint on the origin of the fusion production. This stems from the strong anisotropy in energy created in beam-target fusion, compared to the relatively isotropic emission in thermonuclear fusion. In dense Z-pinch plasmas, a potential and undesirable cause of beam-target fusion reactions is the presence of fast-growing, “sausage” instabilities. This work introduces a new method for characterizing beam instabilities by recording individual neutron interactions in plastic scintillator detectors positioned at two different angles around the device chamber. Histograms of the pulse-integral spectra from the two locations are compared using detailed Monte Carlo simulations. These models infer the deuteron beam energy based on differences in the measured neutron spectra at the two angles, thereby discriminating beam-target from thermonuclear production. An analysis of neutron emission profiles from FuZE precludes the presence of deuteron beams with energies greater than 4.65 keV with a statistical uncertainty of 4.15 keV and a systematic uncertainty of 0.53 keV. This analysis demonstrates that axial, beam-target fusion reactions are not the dominant source of neutron emission from FuZE. These data are promising for scaling FuZE up to fusion reactor conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2009

Bounded Linear Stability Analysis - A Time Delay Margin Estimation Approach for Adaptive Control

This paper presents a method for estimating time delay margin for model-reference adaptive control of systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent the conventional model-reference adaptive law by a locally bounded linear approximation within a small time window using the comparison lemma. The locally bounded linear approximation of the combined adaptive system is cast in a form of an input-time-delay differential equation over a small time window. The time delay margin of this system represents a local stability measure and is computed analytically by a matrix measure method, which provides a simple analytical technique for estimating an upper bound of time delay margin. Based on simulation results for a scalar model-reference adaptive control system, both the bounded linear stability method and the matrix measure method are seen to provide a reasonably accurate and yet not too conservative time delay margin estimation.

Nguyen, Nhan T.↗